Task-Technology Fit in Virtual Reality: Explaining Behavioral Intention to Use and Perceived Performance

While Virtual Reality (VR) is becoming more popular for professional applications, empirical evidence on its task-specific suitability remains scarce. This study employs the Task-Technology Fit (TTF) model to evaluate the perceived fit of VR for workplace tasks using McGrath’s Group Task Circumplex. Results from an online survey were analyzed with Partial Least Squares Structural Equation Modeling (PLS-SEM). They indicate that TTF relates to performance perceptions and behavioral intention to use, explaining a substantial share of variance in both outcomes. The study links task taxonomies to TTF in immersive settings and shows that task and technology characteristics both contribute to perceived fit, with social presence the most salient technology factor. Practically, the findings support task-aware selection and design of VR solutions that align with task profiles. Limitations include simulated (non-headset) stimuli and a personalization-comparability trade-off introduced by task filtering.